The Use of Working Variables in the Bayesian Modeling of Mean and Dispersion Parameters in Generalized Nonlinear Models with Random Effects

DOI10.1080/03610918.2013.770529zbMath1328.62164OpenAlexW1981694486MaRDI QIDQ5252816

Andres Gutierrez

Publication date: 3 June 2015

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610918.2013.770529

zbMATH Keywords

Bayesian analysisheteroscedasticitynonlinear regressiongeneralized linear modelsMCMCmixed effects models

Mathematics Subject Classification ID

Bayesian inference (62F15) General nonlinear regression (62J02)

Cites Work

• Unnamed Item
• Random-Effects Models for Longitudinal Data
• Robust joint modeling of mean and dispersion through trimming
• Nonparametric estimation of mean and dispersion functions in extended generalized linear models
• Generalized linear models
• Overdispersed generalized linear models
• General design Bayesian generalized linear mixed models
• A note on overdispersed exponential families
• The Analysis of Ring-Recovery Data Using Random Effects
• Bayesian Modeling Using WinBUGS
• Bayesian modelling of the mean and covariance matrix in normal nonlinear models
• Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
• Bayesian Measures of Model Complexity and Fit
• A Bayesian Formulation of Exploratory Data Analysis and Goodness‐of‐fit Testing*
• Bayesian Inference for Generalized Linear and Proportional Hazards Models via Gibbs Sampling
• Heteroscedastic Nonlinear Regression Models
• Generalized Linear Models with Random Effects
• Monte Carlo sampling methods using Markov chains and their applications
• Generalized Additive Models for Location, Scale and Shape
• Linear mixed models for longitudinal data

This page was built for publication: The Use of Working Variables in the Bayesian Modeling of Mean and Dispersion Parameters in Generalized Nonlinear Models with Random Effects